Search results for: multi-agent double deep Q-network (MADDQN)

Authors: Xin Shi, Wei Tan, Guorui Zhu

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The contraction-expansion array (CEA) microfluidic device is widely used for particle focusing and particle separation. Without the introduction of external fields, it can manipulate particles using hydrodynamic forces, including inertial lift forces and Dean drag forces. The focusing pattern of the particles in a CEA channel can be affected by the structural parameter, block ratio, and flow streamlines. Here, two typical focusing patterns with five different structural parameters were investigated, and the force mechanism was analyzed. We present nine CEA channels with different aspect ratios based on the process of changing the particle equilibrium positions. The results show that 10-15 μm particles have the potential to generate a side focusing line as the structural parameter (¬R𝓌) increases. For a determined channel structure and target particles, when the Reynolds number (Rₑ) exceeds the critical value, the focusing pattern will transform from a single pattern to a double pattern. The parameter α/R𝓌 can be used to calculate the critical Reynolds number for the focusing pattern transformation. The results can provide guidance for microchannel design and biomedical analysis.

Keywords: microfluidic, inertial focusing, particle separation, Dean flow

Procedia PDF Downloads 72

Authors: Anup Anand Deshmukh, Catherine Soladie, Renaud Seguier

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Emotion plays a key role in many applications like healthcare, to gather patients’ emotional behavior. Unlike typical ASR (Automated Speech Recognition) problems which focus on 'what was said', it is equally important to understand 'how it was said.' There are certain emotions which are given more importance due to their effectiveness in understanding human feelings. In this paper, we propose an approach that models human stress from audio signals. The research challenge in speech emotion detection is finding the appropriate set of acoustic features corresponding to an emotion. Another difficulty lies in defining the very meaning of emotion and being able to categorize it in a precise manner. Supervised Machine Learning models, including state of the art Deep Learning classification methods, rely on the availability of clean and labelled data. One of the problems in affective computation is the limited amount of annotated data. The existing labelled emotions datasets are highly subjective to the perception of the annotator. We address the first issue of feature selection by exploiting the use of traditional MFCC (Mel-Frequency Cepstral Coefficients) features in Convolutional Neural Network. Our proposed Emo-CNN (Emotion-CNN) architecture treats speech representations in a manner similar to how CNN’s treat images in a vision problem. Our experiments show that Emo-CNN consistently and significantly outperforms the popular existing methods over multiple datasets. It achieves 90.2% categorical accuracy on the Emo-DB dataset. We claim that Emo-CNN is robust to speaker variations and environmental distortions. The proposed approach achieves 85.5% speaker-dependant categorical accuracy for SAVEE (Surrey Audio-Visual Expressed Emotion) dataset, beating the existing CNN based approach by 10.2%. To tackle the second problem of subjectivity in stress labels, we use Lovheim’s cube, which is a 3-dimensional projection of emotions. Monoamine neurotransmitters are a type of chemical messengers in the brain that transmits signals on perceiving emotions. The cube aims at explaining the relationship between these neurotransmitters and the positions of emotions in 3D space. The learnt emotion representations from the Emo-CNN are mapped to the cube using three component PCA (Principal Component Analysis) which is then used to model human stress. This proposed approach not only circumvents the need for labelled stress data but also complies with the psychological theory of emotions given by Lovheim’s cube. We believe that this work is the first step towards creating a connection between Artificial Intelligence and the chemistry of human emotions.

Keywords: deep learning, brain chemistry, emotion perception, Lovheim's cube

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Authors: Sayor Ajfar Aaron, Mushfiqur Rahman, Sajjat Hossain Abir, Ashif Newaz

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This study delves into the development of an artificial intelligence application designed for real-time emotion recognition from human vocal patterns. Utilizing advanced machine learning algorithms, including deep learning and neural networks, the paper highlights both the technical challenges and potential opportunities in accurately interpreting emotional cues from speech. Key findings demonstrate the critical role of diverse training datasets and the impact of ambient noise on recognition accuracy, offering insights into future directions for improving robustness and applicability in real-world scenarios.

Keywords: artificial intelligence, convolutional neural network, emotion recognition, vocal patterns

Procedia PDF Downloads 41

Authors: F. Ainlhout, S. Boutaleb, M. C. Diaz-Barradas, M. Zunzunegui

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Argania spinosa is an endemic tree of the southwest of Morocco, occupying 828,000 Ha, distributed mainly between Mediterranean vegetation and the desert. This tree can grow in extremely arid regions in Morocco, where annual rainfall ranges between 100-300 mm where no other tree species can live. It has been designated as a UNESCO Biosphere reserve since 1998. Argania tree is of great importance in human and animal feeding of rural population as well as for oil production, it is considered as a multi-usage tree. Admine forest located in the suburbs of Agadir city, 5 km inland, was selected to conduct this work. The aim of the study was to investigate the temporal variation in root-zone moisture dynamic in response to variation in climatic conditions and vegetation water uptake, using a geophysical technique called Electrical resistivity imaging (ERI). This technique discriminates resistive woody roots, dry and moisture soil. Time-dependent measurements (from April till July) of resistivity sections were performed along the surface transect (94 m Length) at 2 m fixed electrode spacing. Transect included eight Argan trees. The interactions between the tree and soil moisture were estimated by following the tree water status variations accompanying the soil moisture deficit. For that purpose we measured midday leaf water potential and relative water content during each sampling day, and for the eight trees. The first results showed that ERI can be used to accurately quantify the spatiotemporal distribution of root-zone moisture content and woody root. The section obtained shows three different layers: middle conductive one (moistured); a moderately resistive layer corresponding to relatively dry soil (calcareous formation with intercalation of marly strata) on top, this layer is interspersed by very resistant layer corresponding to woody roots. Below the conductive layer, we find the moderately resistive layer. We note that throughout the experiment, there was a continuous decrease in soil moisture at the different layers. With the ERI, we can clearly estimate the depth of the woody roots, which does not exceed 4 meters. In previous work on the same species, analyzing the δ18O in water of xylem and in the range of possible water sources, we argued that rain is the main water source in winter and spring, but not in summer, trees are not exploiting deep water from the aquifer as the popular assessment, instead of this they are using soil water at few meter depth. The results of the present work confirm the idea that the roots of Argania spinosa are not growing very deep.

Keywords: Argania spinosa, electrical resistivity imaging, root system, soil moisture

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Authors: Keyi Wang

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Similar to the touchscreen, hand gesture based human-computer interaction (HCI) is a technology that could allow people to perform a variety of tasks faster and more conveniently. This paper proposes a training method of an image-based hand gesture image and video clip recognition system using a CNN (Convolutional Neural Network) with a dataset. A dataset containing 6 hand gesture images is used to train a 2D CNN model. ~98% accuracy is achieved. Furthermore, a 3D CNN model is trained on a dataset containing 4 hand gesture video clips resulting in ~83% accuracy. It is demonstrated that a Cozmo robot loaded with pre-trained models is able to recognize static and dynamic hand gestures.

Keywords: deep learning, hand gesture recognition, computer vision, image processing

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Authors: Davender Kumar, Virender Singh, Rekha Sharma

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Correction of skeletal deformities in adult patients with orthodontics is limited. In adult severe cases, the combined approach, orthodontic and orthognathic surgery, is always the treatment of choice, and the results obtained usually ensure a better esthetic, functional, and stable results Orthognathic surgery is the best option for cases when camouflage treatment is questionable and growth modulation is not possible. This case report illustrates the benefit of the team approach in correcting mandible retrusion along with class II skeletal deformity with 100% deep bite. Correction was achieved by anterior repositioning of mandible osteotomy along with orthodontic treatment. The patient's facial appearance was markedly improved along with functional and stable occlusion.

Keywords: camouflage, skeletal, orthognathic, dental

Procedia PDF Downloads 423

Authors: Sergio A. Bernal-Chavez, Sergio Alcalá-Alcalá, Doris A. Cerecedo-Mercado, Adriana Ganem-Rondero

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The prevalence of people with chronic wounds has increased dramatically by many factors including smoking, obesity and chronic diseases, such as diabetes, that can slow the healing process and increase the risk of becoming chronic. Because of this situation, the improvement of chronic wound treatments is a necessity, which has led to the scientific community to focus on improving the effectiveness of current therapies and the development of new treatments. The wound formation is a physiological complex process, which is characterized by an inflammatory stage with the presence of proinflammatory cells that create a proteolytic microenvironment during the healing process, which includes the degradation of important growth factors and cytokines. This decrease of growth factors and cytokines provides an interesting strategy for wound healing if they are administered externally. The use of nanometric drug delivery systems, such as polymer nanoparticles (NP), also offers an interesting alternative around dermal systems. An interesting strategy would be to propose a formulation based on a thermosensitive hydrogel loaded with polymeric nanoparticles that allows the inclusion and application of a platelet lysate (PL) on damaged skin, with the aim of promoting wound healing. In this work, NP were prepared by a double emulsion-solvent evaporation technique, using polylactic-co-glycolic acid (PLGA) as biodegradable polymer. Firstly, an aqueous solution of PL was emulsified into a PLGA organic solution, previously prepared in dichloromethane (DCM). Then, this disperse system (W/O) was poured into a polyvinyl alcohol (PVA) solution to get the double emulsion (W/O/W), finally the DCM was evaporated by magnetic stirring resulting in the NP formation containing PL. Once the NP were obtained, these systems were characterized by morphology, particle size, Z-potential, encapsulation efficiency (%EE), physical stability, infrared spectrum, calorimetric studies (DSC) and in vitro release profile. The optimized nanoparticles were included in a thermosensitive gel formulation of Pluronic® F-127. The gel was prepared by the cold method at 4 °C and 20% of polymer concentration. Viscosity, sol-gel phase transition, time of no flow solid-gel at wound temperature, changes in particle size by temperature-effect using dynamic light scattering (DLS), occlusive effect, gel degradation, infrared spectrum and micellar point by DSC were evaluated in all gel formulations. PLGA NP of 267 ± 10.5 nm and Z-potential of -29.1 ± 1 mV were obtained. TEM micrographs verified the size of NP and evidenced their spherical shape. The %EE for the system was around 99%. Thermograms and in infrared spectra mark the presence of PL in NP. The systems did not show significant changes in the parameters mentioned above, during the stability studies. Regarding the gel formulation, the transition sol-gel occurred at 28 °C with a time of no flow solid-gel of 7 min at 33°C (common wound temperature). Calorimetric, DLS and infrared studies corroborated the physical properties of a thermosensitive gel, such as the micellar point. In conclusion, the thermosensitive gel described in this work, contains therapeutic amounts of PL and fulfills the technological properties to be used in damaged skin, with potential application in wound healing and tissue regeneration.

Keywords: growth factors, polymeric nanoparticles, thermosensitive hydrogels, tissue regeneration

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Authors: Helen Pushkarskaya, Michael Smithson, Jane E. Joseph, Christine Corbly, Ifat Levy

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Studies of decision making under uncertainty generally focus on imprecise information about outcome probabilities (“ambiguity”). It is not clear, however, whether conflicting information about outcome probabilities affects decision making in the same manner as ambiguity does. Here we combine functional Magnetic Resonance Imaging (fMRI) and a simple gamble design to study this question. In this design, the levels of ambiguity and conflict are parametrically varied, and ambiguity and conflict gambles are matched on both expected value and variance. Behaviorally, participants avoided conflict more than ambiguity, and attitudes toward ambiguity and conflict did not correlate across subjects. Neurally, regional brain activation was differentially modulated by ambiguity level and aversion to ambiguity and by conflict level and aversion to conflict. Activation in the medial prefrontal cortex was correlated with the level of ambiguity and with ambiguity aversion, whereas activation in the ventral striatum was correlated with the level of conflict and with conflict aversion. This novel double dissociation indicates that decision makers process imprecise and conflicting information differently, a finding that has important implications for basic and clinical research.

Keywords: decision making, uncertainty, ambiguity, conflict, fMRI

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Authors: Rachida Malaoui, Leila Arabet , Asma Benbouza

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The use of mining waste rock as a material for construction is one of the biggest concerns grabbing the attention of many mining countries. As these materials are abandoned, more effective solutions have been made to offset some of the building materials, and to avoid environmental pollution. The sands of the Djemi Djema deposit mines of the Djebel Onk mines are sedimentary materials of several varieties of layers with varying thicknesses and are worth far more than 300m deep. The sands from the Djemi Djema business area are medium to coarse and are discharged and accumulated, generating a huge estimated quantity of more than 77424250 tonnes. This state of "resource" is of great importance so as to be oriented towards the fields of public works and civil engineering after having reached the acceptable properties of this resource

Keywords: reuse, sands, shear tests, waste rock

Procedia PDF Downloads 138

Authors: Beata Cieniawska, Deta Łuczycka, Katarzyna Dereń

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When assessing the quality of the spraying procedure, three indicators are used: uneven distribution of precipitation of liquid sprayed, degree of coverage of sprayed surfaces, and deposition of liquid spraying However, there is a lack of information on the relationship between the quality parameters of the procedure. Therefore, the research was carried out at the Institute of Agricultural Engineering of Wrocław University of Environmental and Life Sciences. The aim of the study was to determine the relationship between the degree of coverage of sprayed surfaces and the deposition of liquid in the aspect of the parametric characteristics of the protected plant using selected single and double stream nozzles. Experiments were conducted under laboratory conditions. The carrier of nozzles acted as an independent self-propelled sprayer used for spraying, whereas the parametric characteristics of plants were determined using artificial plants as the ratio of the vertical projection surface and the horizontal projection surface. The results and their analysis showed a strong and very strong correlation between the analyzed parameters in terms of the characteristics of the sprayed object.

Keywords: degree of coverage, deposition of liquid, nozzle, spraying

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Authors: Linta Rose, Prasad K. Bhaskaran

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Water-level information along the coast is very important for disaster management, navigation, planning shoreline management, coastal engineering and protection works, port and harbour activities, and for a better understanding of near-shore ocean dynamics. The water-level variation along a coast attributes from various factors like astronomical tides, meteorological and hydrological forcing. The study area is the Head Bay of Bengal which is highly vulnerable to flooding events caused by monsoons, cyclones and sea-level rise. The study aims to explore the extent to which wind and surface pressure can influence water-level elevation, in view of the low-lying topography of the coastal zones in the region. The ADCIRC hydrodynamic model has been customized for the Head Bay of Bengal, discretized using flexible finite elements and validated against tide gauge observations. Monthly mean climatological wind and mean sea level pressure fields of ERA Interim reanalysis data was used as input forcing to simulate water-level variation in the Head Bay of Bengal, in addition to tidal forcing. The output water-level was compared against that produced using tidal forcing alone, so as to quantify the contribution of meteorological forcing to water-level. The average contribution of meteorological fields to water-level in January is 5.5% at a deep-water location and 13.3% at a coastal location. During the month of July, when the monsoon winds are strongest in this region, this increases to 10.7% and 43.1% respectively at the deep-water and coastal locations. The model output was tested by varying the input conditions of the meteorological fields in an attempt to quantify the relative significance of wind speed and wind direction on water-level. Under uniform wind conditions, the results showed a higher contribution of meteorological fields for south-west winds than north-east winds, when the wind speed was higher. A comparison of the spectral characteristics of output water-level with that generated due to tidal forcing alone showed additional modes with seasonal and annual signatures. Moreover, non-linear monthly mode was found to be weaker than during tidal simulation, all of which point out that meteorological fields do not cause much effect on the water-level at periods less than a day and that it induces non-linear interactions between existing modes of oscillations. The study signifies the role of meteorological forcing under fair weather conditions and points out that a combination of multiple forcing fields including tides, wind, atmospheric pressure, waves, precipitation and river discharge is essential for efficient and effective forecast modelling, especially during extreme weather events.

Keywords: ADCIRC, head Bay of Bengal, mean sea level pressure, meteorological forcing, water-level, wind

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Authors: Marta Cordero-Gracia, Mariola Gomez, Olivier Blesbois, Marina Carrion

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One of the difficulties in icing simulations is for extended periods of exposure, when very large ice shapes are created. As well as being large, they can have complex shapes, such as a double horn. For icing simulations, these configurations are currently computed in several steps. The icing step is stopped when the ice shapes become too large, at which point a new mesh has to be created to allow for further CFD and ice growth simulations to be performed. This can be very costly, and is a limiting factor in the simulations that can be performed. A way to avoid the costly human intervention in the re-meshing step of multistep icing computation is to use mesh deformation instead of re-meshing. The aim of the present work is to apply an interpolation method based on Radial Basis Functions (RBF) to transfer deformations from surface mesh to volume mesh. This deformation tool has been developed specifically for icing problems. It is able to deal with localized, sharp and large deformations, unlike the tools traditionally used for more smooth wing deformations. This tool will be presented along with validation on typical two-dimensional icing shapes.

Keywords: ice accretion, interpolation, mesh deformation, radial basis functions

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Authors: Wang Zhenzhen, Wang Xu, Hong Liangping

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The construction of thematic commercial streets has been on the hotspot with the rapid development of cities. In order to improve the image and competitiveness of cities, many cities are building or rebuilding thematic commercial streets. However, many contradictions and problems have emerged during this process. Therefore, it is significant, for both the practice and the research, to analyse the development of thematic commercial streets and provide some useful suggestions. Through the deep research and comparative study of the eight typical thematic commercial streets in Harbin, this paper summarize the current situations, laws and influencing factors of the development of these streets, and then put forward some suggestions about the plan, constructions and developments of the thematic commercial streets.

Keywords: thematic commercial streets, laws of the development, influence factors, the constructions and developments, degrees of aggregation

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Authors: Amdy Moustapha Drame, Ilya V. Germashev, E. A. Markushevskaya

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Among the main problems of medicine is breast cancer, from which a significant number of women around the world are constantly dying. Therefore, the detection of malignant breast tumors is an urgent task. For many years, various technologies for detecting these tumors have been used, in particular, in thermal imaging in order to determine different levels of breast cancer development. These periodic screening methods are a diagnostic tool for women and may have become an alternative to older methods such as mammography. This article proposes a model for the identification of malignant neoplasms of the mammary glands by the asymmetry of internal and external thermal imaging fields.

Keywords: asymmetry, breast cancer, tumors, deep learning, thermogram, convolutional transformation, classification

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Authors: Tim Farrelly

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In recent years, AI-powered object detection systems have opened the doors for innovative new applications and products, especially those operating in the real world or ‘on edge’ – namely, in sport. This paper investigates the viability of an ultra-low parameter convolutional neural network specially designed for the detection of footballs on ‘on the edge’ devices. The main contribution of this paper is the exploration of integrating new design features (depth-wise separable convolutional blocks and squeezed and excitation modules) into an ultra-low parameter network and demonstrating subsequent improvements in performance. The results show that tracking the ball from Full HD images with negligibly high accu-racy is possible in real-time.

Keywords: deep learning, object detection, machine vision applications, sport, network design

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Authors: Divvela Vishnu Sai Kumar, Deepak Arora, Sheenu Rizvi

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Forecasting a cyclone through satellite images consists of the estimation of the intensity of the cyclone and predicting it before a cyclone comes. This research work can help people to take safety measures before the cyclone comes. The prediction of the intensity of a cyclone is very important to save lives and minimize the damage caused by cyclones. These cyclones are very costliest natural disasters that cause a lot of damage globally due to a lot of hazards. Authors have proposed five different CNN (Convolutional Neural Network) models that estimate the intensity of cyclones through INSAT-3D IR images. There are a lot of techniques that are used to estimate the intensity; the best model proposed by authors estimates intensity with a root mean squared error (RMSE) of 10.02 kts.

Keywords: estimating cyclone intensity, deep learning, convolution neural network, prediction models

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Authors: Sapan Bhatnagar, Danish Akhtar, Salman Ahmed, Asif Ekbal, Gufran Beig

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Particulates are the solid and liquid droplets present in the atmosphere, they have serious negative effects on human health and environment. PM10 and PM2.5 are so small that they can penetrate deep into our lungs through the respiratory system. Determination of the amount of particulates present in the atmosphere per cubic meter is necessary to monitor, regulate and model atmospheric particulate levels. Air Quality Index is an index tells us how clean or polluted our air is, and what associated health effects might be a concern for us. The AQI focuses on health affects you may experience within a few hours or days after breathing polluted air. The quality rating for each pollutant was calculated. The geometric mean of these quality ratings gives the Air Quality Index. The existing concentrations of pollutants were compared with ambient air quality standards.

Keywords: air quality index, particulate, respirable dust sampler, dust sampler

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Authors: Hsiao-Yung Wang

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This paper aims to elaborate the standpoint of neo-Marxism of Russian philosopher Mikhail Bakhtin by critical reading his concept of Bildungsroman; thereby, it aims to map the theoretical implication of spatial rhetoric and its time politics/emancipatory politics in late Bakhtin’s thought. First, it aims to outline the two revolving rings of spatiality in Bildungsroman, proceeding from 'recollecting the past' to 'foreseeing the future' on the basis of visuality and materialistic realism. Herein, Bakhtin has temporarily been leaving his previous research concern on polyphonic novel. Second, it aims to demonstrate that although Bakhtin has constantly emphasized the necessity of reconstructing opened future space, his insistence on 'emergence' has still generated a seemingly theoretical lacuna which needs to be filled. 'Doubled heterotopia,' as popularized by contemporary rhetorician Saindon, might be an adequate approach to articulate and present the rhetorical functions and dynamics of Bakhtin’s spatial rhetoric dialectically. Based on the research findings, this paper argues that Bakhtin indeed attempted to go beyond the deterministic model of Marxism and neo-Marxism strategically and reciprocally.

Keywords: Bildungsroman, double heterotopia, emergence, Mikhail Bakhtin, neo-Marxism, spatial rhetoric, time-politics, visuality

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Authors: Mounir Zekkaoui, Abdelhadi Fennan

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The software evolution control requires a deep understanding of the changes and their impact on different system heterogeneous artifacts. And an understanding of descriptive knowledge of the developed software artifacts is a prerequisite condition for the success of the evolutionary process. The implementation of an evolutionary process is to make changes more or less important to many heterogeneous software artifacts such as source code, analysis and design models, unit testing, XML deployment descriptors, user guides, and others. These changes can be a source of degradation in functional, qualitative or behavioral terms of modified software. Hence the need for a unified approach for extraction and representation of different heterogeneous artifacts in order to ensure a unified and detailed description of heterogeneous software artifacts, exploitable by several software tools and allowing to responsible for the evolution of carry out the reasoning change concerned.

Keywords: heterogeneous software artifacts, software evolution control, unified approach, meta model, software architecture

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Authors: Bokku Kang, Changsoo Chon, Han Sung Kim

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We developed new design of rod of pedicle screw system that is beneficial in maintaining the spacing between the vertebrae and assessed the performance of the posterior fixation screw systems by numerical analysis according to the range of motion (flexion, extension, lateral bending, and axial rotation) of the vertebral column after inserting the pedicle screws. The simulation results showed that the conventional rod was the most low equivalent stress value among implant units in the case of flexion, extension and lateral bending of the vertebrae. In all cases except the torsional rotation, the results showed that the stress level of the single and double rounded rod exceeded about 30% to 70% compare to the conventional rod. Therefore, this product is not suitable for actual application in the field yet and it seems that product design optimization is necessary. Acknowledgement: This research was supported by the Ministry of Trade, Industry & Energy (MOTIE), Korea Institute for Advancement of Technology (KIAT) through the Encouragement Program for The Industries of Economic Cooperation Region.

Keywords: lumber spine, internal fixation device, finite element method, biomechanics

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Authors: Abdulwakeel B. Raji

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This paper introduces a concept of an intelligent virtual learning environment that involves communication between learners and an artificially intelligent teaching agent in an attempt to replicate classroom learning interactions. The benefits of this technology over current e-learning practices is that it creates a virtual classroom where real time adaptive learning interactions are made possible. This is a move away from the static learning practices currently being adopted by e-learning systems. Over the years, artificial intelligence has been applied to various fields, including and not limited to medicine, military applications, psychology, marketing etc. The purpose of e-learning applications is to ensure users are able to learn outside of the classroom, but a major limitation has been the inability to fully replicate classroom interactions between teacher and students. This study used comparative surveys to gain information and understanding of the current learning practices in Nigerian universities and how they compare to these practices compare to the use of a developed e-learning system. The study was conducted by attending several lectures and noting the interactions between lecturers and tutors and as an aftermath, a software has been developed that deploys the use of an artificial intelligent teaching-agent alongside an e-learning system to enhance user learning experience and attempt to create the similar learning interactions to those found in classroom and lecture hall settings. Dialogflow has been used to implement a teaching-agent, which has been developed using JSON, which serves as a virtual teacher. Course content has been created using HTML, CSS, PHP and JAVASCRIPT as a web-based application. This technology can run on handheld devices and Google based home technologies to give learners an access to the teaching agent at any time. This technology also implements the use of definite clause grammars and natural language processing to match user inputs and requests with defined rules to replicate learning interactions. This technology developed covers familiar classroom scenarios such as answering users’ questions, asking ‘do you understand’ at regular intervals and answering subsequent requests, taking advanced user queries to give feedbacks at other periods. This software technology uses deep learning techniques to learn user interactions and patterns to subsequently enhance user learning experience. A system testing has been undergone by undergraduate students in the UK and Nigeria on the course ‘Introduction to Database Development’. Test results and feedback from users shows that this study and developed software is a significant improvement on existing e-learning systems. Further experiments are to be run using the software with different students and more course contents.

Keywords: virtual learning, natural language processing, definite clause grammars, deep learning, artificial intelligence

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Authors: Özge Çeliker Tosun, Melda Başer Secer, İsmail Düşmez, Sedat Çapar, İlkay Kozak, Melahat Aktaş, Furkan Can Şimşek, Gökhan Tosun

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Purpose: Portable innovative balance room system with digital game program; It was created to be able to be divided into small areas, such as inside the house, garden, balcony, to enable the person to enter and perform both evaluation and exercise safely, and to ensure that these results can be stored and sent to the therapist live or later when desired. The aim is to compare the effectiveness of the exercise program applied by the elderly within this system and the exercise program implemented under the supervision of a physiotherapist on balance and urinary incontinence symptoms. Materials and Methods: The study was conducted in a randomized controlled manner on 63 people with urinary incontinence (mean age: 75.5 years) at Narlıdere Nursing Home Elderly Care and Rehabilitation Center. Elderly people participating in the study were divided into 3 groups: 1. Group, an exercise program consisting of pelvic floor muscle training and OTOGA exercises, 2. Group, only pelvic floor muscle training, and 3. Group, pelvic floor muscle training and Otoga exercises in the form of a digital game program in a portable balance room system. (self-administered) for 12 weeks. Pelvic floor distress inventory (PTDE-20) and bladder diary were used to evaluate the incontinance symptoms of the cases. Pelvic floor muscle function was evaluated with superficial EMG. Berg, Fall Effectiveness Scale (FES) and Functional Status Evaluations (Chair Stand Test, Eight (8) Food Up and Go Test, Chair Sit and Reach Test, Two Minutes Step Test) were used to evaluate balance. The existence of differences between groups was analyzed using Krusskal Wallis analysis of variance, and the difference between before and after exercise was analyzed with Wilcoxon tests. Results: After treatment, PTDE-20, daily urinary incontinence and toilet visits values decreased significantly in all three groups (p < 0.001). While there was a statistically significant increase in pelvic floor muscle EMG values in the 2nd and third groups after treatment, there was no change in the other group (2nd Group PFM average EMG before-after: 5.5 (4.15-10.95) - 10.95 (8.68-13.68), P=0.05, 3 Group PFM average EMG before-after: 6.5 (4.28-11.55) - 11.75 (8.67-14.26), p=0.04). While BERG score, Chair Stand Test, Eight (8) Food Up and Go Test, and Two Minutes Step Test values increased in all groups (p<0.05), Fall Effectiveness Scale (FES) values did not change after treatment. Conclusion: Although pelvic floor muscle training combined with balance exercises reduces symptoms, it may not lead to a positive improvement in the functions of the pelvic floor muscles. For this reason, recovery lasts for a short time, and then symptoms may reoccur in the future. However, thanks to the new system, when balance exercises are combined with a game program for the pelvic floor muscles, a double effect can be achieved with a single application and both incontinence and balance problems can be treated in a safe environment where the person can do it himself. But more work needs to be done on this subject. However, thanks to the new system, a double effect can be achieved with a single application, and both incontinence and balance problems can be treated in a safe environment where the person can do it himself. But more work needs to be done on new system

Keywords: fall, urinary incontinance, balance, elderly

Procedia PDF Downloads 66

Authors: Pei-Lin Yueh, Bor-Yann Chen, Chuan-Chung Hsueh

Abstract:

This first-attempt study revealed that decolorized intermediates of azo dyes could act as redox mediators to assist wastewater (WW) decolorization due to enhancement of electron-transport phenomena. Electrochemical impedance spectra indicated that hydroxyl and amino-substituent(s) were functional group(s) as redox-mediator(s). As azo dyes are usually multiple benzene rings structured, their derived decolorized intermediates are likely to play roles of electron shuttles due to lower barrier of energy gap for electron shuttling. According to cyclic voltammetric profiles, redox-mediating characteristics of decolorized intermediates of azo dyes (e.g., RBu171, RR198, RR141, and RBk5) were clearly disclosed. With supplementation of biodecolorized metabolites of RR141 and 198, decolorization performance of could be evidently augmented. This study also suggested the optimal modes of microbial fuel cell (MFC)-assisted WW decolorization would be plug-flow or batch mode of operation with no mix. Single chamber-MFCs would be more favourable than double chamber MFCs due to non-mixing contacting reactor scheme for operation.

Keywords: redox mediators, dye decolorization, bioelectricity generation, microbial fuel cells

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Authors: Nidhal K. Azawi, John M. Gauch

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Colorectal cancer is one of the leading causes of cancer death in the US and the world, which is why millions of colonoscopy examinations are performed annually. Unfortunately, noise, specular highlights, and motion artifacts corrupt many images in a typical colonoscopy exam. The goal of our research is to produce automated techniques to detect and correct or remove these noninformative images from colonoscopy videos, so physicians can focus their attention on informative images. In this research, we first automatically extract features from images. Then we use machine learning and deep neural network to classify colonoscopy images as either informative or noninformative. Our results show that we achieve image classification accuracy between 92-98%. We also show how the removal of noninformative images together with image alignment can aid in the creation of image panoramas and other visualizations of colonoscopy images.

Keywords: colonoscopy classification, feature extraction, image alignment, machine learning

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Authors: Julie De Pril, Cécile Godfroid

Abstract:

Nowadays, achieving double bottom line has become a widely recognized objective for microfinance institutions (MFIs). They would like to be financially sustainable or even profitable while continuing to focus on their social mission. In order to rise their financial performance, MFIs tend to grant financial bonuses to loan officers so that they increase their performance and efficiency. However, as argued by motivation crowding theory, monetary rewards may not have only positive effects but can also erode intrinsic motivation. Since MFIs pursue social objectives in addition to their financial ones, their employees’ intrinsic motivations may include the willingness to help others, like in many non-profit organizations. This is called pro-social motivation in the psychology literature. Particularly, this type of motivation should be highly reflected among microfinance loan officers as a part of their role consists in improving clients’ welfare. Therefore, it seems to be crucial for MFIs to find an equilibrium between the efficiency benefits obtained thanks to the granting of financial incentives and the deterioration of social performance that may result from the reduction of the loan officers’ pro-social motivation. This paper attempts to suggest, with a mathematical model, an optimal incentive scheme MFIs could rely on.

Keywords: loan officers, microfinance, prosocial motivation, rewards

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Authors: Razieh Niazmand, Dina Sadat Mousavian, Parvin Sharayei

Abstract:

This study investigated the effect of carboxymethyl cellulose (CMC), tragacanth, and saalab hydrocolloids in two concentrations (0.3%, 0.7%) and different frying media, refined canola oil (RCO), RCO + 1% bene kernel oil (BKO), and RCO + 1 mg/l unsaponifiable matter (USM) of BKO on acrylamide formation in fried potato slices. The hydrocolloid coatings significantly reduced acrylamide formation in potatoes fried in all oils. Increasing the hydrocolloid concentration from 0.3% to 0.7% produced no effective inhibition of acrylamide. The 0.7 % CMC solution was identified as the most promising inhibitor of acrylamide formation in RCO oil, with a 62.9% reduction in acrylamide content. The addition of BKO or USM to RCO led to a noticeable reduction in the acrylamide level in fried potato slices. The findings suggest that a 0.7% CMC solution and RCO+USM are promising inhibitors of acrylamide formation in fried potato products.

Keywords: CMC, frying, potato, saalab, tracaganth

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Authors: Adrienn Novák

Abstract:

The field research was carried out at the Látókép AGTC KIT research area of the University of Debrecen in Eastern-Hungary, on the area of the aeolain loess of the Hajdúság. We examined the effects of the sowing time on the phytopathogenic characteristics and yield production by applying various fertilizer treatments on two different sunflower genotypes (NK Ferti, PR64H42) in 2012 and 2013. We applied three different sowing times (early, optimal, late) and two different treatment levels of fungicides (control = no fungicides applied, double fungicide protection). During our investigations, the studied cropyears were of different sowing time optimum in terms of yield amount (2012: early, 2013: average). By Pearson’s correlation analysis, we have found that delaying the sowing time pronouncedly decreased the extent of infection in both crop years (Diaporthe: r=0.663**, r=0.681**, Sclerotinia: r=0.465**, r=0.622**). The fungicide treatment not only decreased the extent of infection, but had yield increasing effect too (2012: r=0.498**, 2013: r=0.603**). In 2012, delaying of the sowing time increased (r=0.600**), but in 2013, it decreased (r= 0.356*) the yield amount.

Keywords: fungicide treatment, genotypes, sowing time, yield, sunflower

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Authors: Amar Partap Singh Pharwaha, Balkrishan Jindal

Abstract:

In this paper, a new method is developed for hiding image in a digital image with multilayer security. In the proposed method, the secret image is encrypted in the first instance using a flexible matrix based symmetric key to add first layer of security. Then another layer of security is added to the secret data by encrypting the ciphered data using Pythagorean Theorem method. The ciphered data bits (4 bits) produced after double encryption are then embedded within digital image in the spatial domain using Least Significant Bits (LSBs) substitution. To improve the image quality of the stego-image, an improved form of pixel adjustment process is proposed. To evaluate the effectiveness of the proposed method, image quality metrics including Peak Signal-to-Noise Ratio (PSNR), Mean Square Error (MSE), entropy, correlation, mean value and Universal Image Quality Index (UIQI) are measured. It has been found experimentally that the proposed method provides higher security as well as robustness. In fact, the results of this study are quite promising.

Keywords: Pythagorean theorem, pixel adjustment, ciphered data, image hiding, least significant bit, flexible matrix

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Authors: Adam Bownik, Małgorzata Adamczuk, Barbara Pawlik-Skowrońska

Abstract:

Certain strains of cyanobacteria, microorganisms forming water blooms, produce toxic secondary metabolites. Although various effects of cyanotoxins in aquatic animals are known, little data can be found on the influence of some cyanobacterial oligopeptides beyond microcystins. The aim of the present study was to determine the toxicity of novel pure cyanobacterial oligopeptides: microginin FR-1 (MGFR1) and anabaenopeptin-A (ANA-A) on a transparent model rotifer Brachionus calyciflorus with the use of fluorescent double staining with Hoechst 34580 and propidium iodide. The obtained results showed that both studied oligopeptides decreased the fluorescence intensity of animals stained with Hoechst 34580 in a concentration-dependent manner. On the other hand, a concentration-dependent increase of propidium iodide fluorescence was noted in the exposed rotifers. The results suggest that MGFR-1 and ANA-A should be considered as a potent toxic agent to freshwater rotifers, and fluorescent staining with Hoechst and propidium iodide may be a valuable tool for determination of toxicity of cyanobacterial oligopeptides in rotifers.

Keywords: cyanobacteria, brachionus, oligopeptides, fluorescent staining, hoechst, propidium iodide

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Authors: Ulrike Dowie, Ralph Grothmann

Abstract:

Rational planning decisions are based upon forecasts. Precise forecasting has, therefore, a central role in business. The prediction of customer demand is a prime example. This paper introduces recurrent neural networks to model customer demand and combines the forecast with uncertainty measures to derive decision support of the demand planning department. It identifies and describes the keys to the successful implementation of an AI-based solution: bringing together data with business knowledge, AI methods, and user experience, and applying agile software development practices.

Keywords: agile software development, AI project success factors, deep learning, demand forecasting, forecast uncertainty, neural networks, supply chain management

Procedia PDF Downloads 178